Breath testing has long been recognized as a reliable technique for diagnosing certain medical conditions through the detection of specific volatile metabolites in exhaled breath (Buszewski et al., Biomed. Chromatogr., 2007, 21, 553-566). The analysis of breath offers several advantages being a non-invasive technique that possess the potential for direct and real-time monitoring (Cao et al., Crit. Rev. Analy. Chem., 2007, 37, 3-13).
Although exhaled breath is mainly composed of N2, O2, CO2, water vapors and other atmospheric constituents (e.g., argon and the like), many volatile compounds which are produced by metabolic processes within the body are found therein. Such metabolic mixtures are relatively less complicated than those obtained from serum or urine samples, and include nitric oxide, nitrogen dioxide, sulfur-conta ining compounds, hydrogen peroxide, carbon monoxide, hydrogen, ammonia, ketones, aldehydes, esters, and alkanes.
Mixtures containing unique compositions of metabolites are indicative of various medical conditions including tissue inflammation (e.g., asthma), immune responses (to cancer cells or bacteria), metabolic disorders (e.g., diabetes), digestive processes, liver and kidney dysfunction, cardiac disorders, gum disease, as well as other physiological conditions. Moreover, mixtures of volatile compounds are characteristic of a certain disease and often display different patterns at different stages of the disease.
Detection of volatile compounds as biomarkers for the diagnosis of medical conditions can be performed using olfactometry systems. These systems, also known as electronic nose devices perform odor detection through the use of an array of cross-reactive sensors in conjunction with pattern recognition algorithms. In contrast to the hitherto “lock-and-key” based devices, wherein each sensor produces an electronic response from a single analyte, in the electronic nose device each sensor is widely responsive to a variety of odorants. In this architecture, each analyte produces a distinct signature from the array of broadly cross-reactive sensors. This configuration allows to considerably widen the variety of compounds to which a given matrix is sensitive, to increase the degree of component identification and, in specific cases, to perform an analysis of individual components in complex multi-component mixtures. Pattern recognition algorithms can then be applied to the entire set of signals, obtained simultaneously from all the sensors in the array, in order to glean information on the identity, properties and concentration of the vapor exposed to the sensor array. Various algorithms and computer controlled systems for olfactometry known in the art are disclosed, for example, in U.S. Pat. Nos. 6,411,905, 6,606,566, 6,609,068, 6,620,109, 6,767,732, 6,820,012, and 6,839,636.
US Patent Application No. 2002/0117659 discloses electrical devices comprised of selectively functionalized nanowires or nanotubes for the detection of analytes.
U.S. Pat. No. 7,153,272 provides methods of collecting and detecting compounds in a human breath sample, comprising a breath collector and a breath analyzer with a plurality of sensors. The methods are directed towards detecting breath compounds for monitoring various medical conditions.
U.S. Pat. No. 7,076,371 discloses methods for characterizing a particular condition or disease from a set of volatile markers which are found, for instance, in the exhaled breath of a person. These markers are detected using a volatile substance detector, such as an artificial olfactory system that includes an artificial neural network/fuzzy filter system equipped with an algorithm for general screening or accurate diagnosis and monitoring, according to need.
U.S. Pat. No. 7,052,854 discloses systems and methods for ex vivo diagnostic analysis of samples of bodily fluids, including exhaled breath. The diagnosis is performed using nanostructure-based assemblies in combination with sensor technology to provide identification of a target analyte/biomarker in a sample.
US Patent Application No. 2007/0048180 discloses a breath analyzer comprising nano-electronic sensors for detecting analytes in human breath. The analyzer contains an integrated multivalent monitor system equipped with a microprocessor capable of analyzing measurements and storing measurement history. The system allows for two or more analytes to be measured in breath samples, and is directed to monitor pulmonary conditions such as asthma.
The analysis of organic vapors in exhaled breath was performed using an array of four polymer-coated surface acoustic wave (SAW) sensors and a thermally desorbable adsorbent pre-concentrator for rapid breath analysis (Groves et al., Analy. Chimi. Acta., 1998, 371, 131-143). The adsorbent used in the pre-concentrator was found critical for achieving adequate sensitivity and further compensate for the high background of water vapors.
Recent studies of gas-chromatography linked to mass-spectrometery (GC-MS) showed that several breath analytes appear to be elevated in instances of lung cancer. Additionally, these analytes are usually detected in distinctive mixture compositions indicative of lung cancer.
Lung cancer was detected by analyzing the breath of patients using a GC column coupled with arrays of polymer-coated surface acoustic wave (Yu et al., Proc. IEEE Sens., 2003, 2, 1333-1337). An artificial neural network has been used, instead of an alveolar gradient, in order to separate the samples into healthy and diseased populations. Using a breath pre-concentrator prior to the GC column, a group of volatile organic compounds characteristic of lung cancer was identified.
In another study, an array of coated quartz crystal microbalance (QCM) sensors was used to detect lung cancer in patients immediately prior to surgical procedure for removing the tumor (Natale et al., Biosens. Bioelectron., 2003, 18(10), 1209-1218). The measurements used the QCM array with no pre-concentration of the breath. The analytes detected by the QCM showed a unique signature.
Recently, sensor arrays of carbon nanotubes coated with different non-polymeric organic layers were shown to be highly potent for the diagnosis of lung cancer via breath samples (Peng et al., Nano Lett., 2008, 8, 3631-3635 and Peng et al., Nano Lett., 2009, 9(4), 1362-1368, published after the priority date of the present application), the contents of which are incorporated by reference herein in their entirety as if fully set forth herein.
In yet another study, carbon nanotubes functionalized with self-assembled sponge like structures of discotic hexa-peri-hexabenzocoronene (HBC) derivatives increased the sensitivity as well as selectivity of the carbon nanotubes to specific VOCs indicative of cancerous breath (Zilberman et al., Langmuir, 2009, 25(9), 5411-5416, published after the priority date of the present application), the contents of which is incorporated by reference herein in its entirety as if fully set forth herein.
There still remains an unmet need for apparatuses and methods for detecting minute quantities of analytes released from human breath with high sensitivity. Furthermore, the advantages of these apparatuses and methods would be particularly striking for measuring mixtures of volatile organic compounds indicative of various types of cancers.